DocumentCode
681404
Title
Detection, localization and pose classification of ear in 3D face profile images
Author
Jiajia Lei ; Jindan Zhou ; Abdel-Mottaleb, Mohamed ; Xinge You
fYear
2013
fDate
15-18 Sept. 2013
Firstpage
4200
Lastpage
4204
Abstract
We present an efficient and robust system for landmark localization, segmentation and pose classification of ears from 3D profile facial range data. After defining 18 landmarks on the ear, including Triangular Fossa and Incisure Intertragica, a novel Ear Tree-structured Graph (ETG) is proposed to represent the 3D ear. We trained a flexible mixture model to locate these landmarks automatically. Afterwards, the ear region is outlined as the minimum rectangle including all landmarks. Finally, by calculating the turning angle between landmarks on the helix, the ear is classified as either a left or a right ear. To the best of our knowledge, there is no previous work on automatic landmark localization for 3D ear on 3D facial profile depth images. Experiments are conducted on University of Notre Dame Collection F and Collection J2 datasets, containing large occlusion, scale and pose variations. Results demonstrate the effectiveness of the proposed techniques.
Keywords
image classification; image segmentation; object detection; pose estimation; trees (mathematics); 3D face profile depth image; Collection F datasets; Collection J2 datasets; University of Notre Dame; ear detection; ear localization; ear pose classification; ear tree-structured graph; flexible mixture model; incisure intertragica; landmark localization; landmark segmentation; left ear; minimum rectangle; occlusion variation; pose variation; right ear; scale variation; triangular fossa; turning angle; Landmark localization; ear detection; ear tree-structured graph; flexible mixture model; pose classification;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing (ICIP), 2013 20th IEEE International Conference on
Conference_Location
Melbourne, VIC
Type
conf
DOI
10.1109/ICIP.2013.6738865
Filename
6738865
Link To Document